Linked Life Data

19140668

Source:http://linkedlifedata.com/resource/pubmed/id/19140668

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2009-6-17
pubmed:abstractText
A computational molecular network analysis of various high-throughput screening (HTS) data sets including inhibition assays and cell-based screens organizes screening hits according to different local structure-activity relationships (SARs). The resulting network representations make it possible to focus on different local SAR environments in screening data. We have designed a simple scoring function accounting for similarity and potency relationships among hits that identifies SAR pathways leading from active compounds in different SAR contexts to key compounds forming activity cliffs. From these pathways, SAR information can be extracted and utilized to select hits for further analysis. In clusters of hits related by different local SARs, alternative pathways can be systematically explored and ranked according to SAR information content, which makes it possible to prioritize hits in a consistent manner.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1520-4804
pubmed:author
pubmed:issnType
Electronic
pubmed:day
26
pubmed:volume
52
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1075-80
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Elucidation of structure-activity relationship pathways in biological screening data.
pubmed:affiliation
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.
pubmed:publicationType
Journal Article